Tag: affect

Push notifications are increasingly being used to engage mobile device users with app content. News organizations deliver breaking-news notifications, social platforms inform about new content, games inform about status updates game, etc … with the goal of making the user engage with the service.

In this research, we – Kostadin Kushlev, University of Virginia, Bruno Cardoso, KU Leuven, and myself – explored to what extent users’ current affect, that is, how they are feeling, impacts user engagement. To this end, we analyzed data from a study conducted by Telefónica Research where the participants (N = 337) downloaded a custom-developed app that delivered notifications.

After attending to a notification (N = 32,704), participants reported how they felt in a mini questionnaire. Besides asking how the participants felt, the questionnaire also offered them to voluntarily engage with further content. Participants were not aware that we our main interest was in observing their interaction with said content — they believed that it was mainly there as a courtesy to make their participation in the study more fun.

Participants always had two choices: a mentally demanding and a simple/diverting task. The tasks in these groups were chosen from a list of 4 options each. The mentally demanding offers included: browsing trending games on Google Play, reading the Wikipedia article of the day, filling out a personality questionnaire, or playing a thinking game. The simple and diverting option included watching a trending video, reading fun facts, playing an action game, and watching trending gif images.

The results show a clear impact of affect on the choice of the content:

When feeling good, people tend to avoid mentally demanding tasks. Hence, proactive recommendations for content that requires mental effort should target moments of neutral or even negative valence.

When tense, people tend to avoid diverting tasks. Thus, people who want to reduce task-induced stress might want to rely on external timers to schedule regular breaks with fun activities.

When energetic, people tend to avoid suggestions for further distraction altogether. Hence, proactive recommendations should target moments of low energetic arousal, such as moments of boredom.

These findings show that the current emotional state affects the kind of content users choose to engage with. Future “smart” devices should not only be technologically smart, but also psychologically smart. They should strive to understand how users feel in order to engage them with the most appropriate content at the most opportune of times.